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|Title:||Embedded virtualization of a hybrid ARM - FPGA computing platform||Authors:||Pham, Dang Khoa||Keywords:||DRNTU::Engineering::Computer science and engineering::Hardware||Issue Date:||2014||Source:||Pham, D. K. (2014). Embedded virtualization of a hybrid arm - FPGA computing platform. Master's thesis, Nanyang Technological University, Singapore.
Pham, D. K. (2014). Embedded virtualization of a hybrid ARM - FPGA computing platform. Master’s thesis, Nanyang Technological University, Singapore.
|Abstract:||Embedded virtualization is a promising solution for several big challenges in embedded systems, such as ECU consolidation, real-time industrial control, software complexity, safety, security and robustness. However, existing virtualization techniques for embedded systems only consider CPU-based processing solutions. With the trend towards hybrid computing platforms, virtualizing the conventional general purpose microprocessor (the software part) without considering the FPGA (the hardware part) only addresses part of the problem. This thesis aims to propose a new approach to embedded virtualization by applying the microkernel-based hypervisor to a hybrid ARM – FPGA platform in order to virtualize both software and hardware tasks. This work involves firstly porting a traditional microkernel-based hypervisor (in this case CODEZERO) to an ARM-based dual core processor on a hybrid computing platform (the Xilinx Zynq 7000). We then examine the necessary modifications to the hypervisor’s driver and APIs in order to support the FPGA hardware of the hybrid platform. An integrated hardware accelerator running on the FPGA under hypervisor control is developed as a prototype to evaluate the ability and functionality of the modified hypervisor. In order to compare the performance and hardware utilization of the hypervisor to Embedded Linux, the context switch overhead and the idle time of the hardware module are examined. Experimental results are presented that show CODEZERO is able to switch hardware contexts two to three orders of magnitude faster than that of Embedded Linux.||URI:||https://hdl.handle.net/10356/55366||DOI:||10.32657/10356/55366||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCSE Theses|
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